"""
Pandas Tools - Data Analysis and DataFrame Operations
This example demonstrates how to use PandasTools for data manipulation and analysis.
Shows enable_ flag patterns for selective function access.
PandasTools is a small tool (<6 functions) so it uses enable_ flags.
Run: `uv pip install pandas` to install the dependencies
"""
from agno.agent import Agent
from agno.tools.pandas import PandasTools
# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
agent_full = Agent(
tools=[PandasTools()], # All functions enabled by default
description="You are a data analyst with full pandas capabilities for comprehensive data analysis.",
instructions=[
"Help users with all aspects of pandas data manipulation",
"Create, modify, analyze, and visualize DataFrames",
"Provide detailed explanations of data operations",
"Suggest best practices for data analysis workflows",
],
markdown=True,
)
# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
print("=== DataFrame Creation and Analysis Example ===")
agent_full.print_response("""
Please perform these tasks:
1. Create a pandas dataframe named 'sales_data' using DataFrame() with this sample data:
{'date': ['2023-01-01', '2023-01-02', '2023-01-03', '2023-01-04', '2023-01-05'],
'product': ['Widget A', 'Widget B', 'Widget A', 'Widget C', 'Widget B'],
'quantity': [10, 15, 8, 12, 20],
'price': [9.99, 15.99, 9.99, 12.99, 15.99]}
2. Show me the first 5 rows of the sales_data dataframe
3. Calculate the total revenue (quantity * price) for each row
""")
